GOseq – Gene Ontology (GO) analysis on RNA-seq data

GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts.

The authors have developed a statistical methodology that enables the application of GO analysis to RNA-seq data by properly incorporating the effect of selection bias. Using published RNA-seq data, they show that accounting for this effect leads to significantly different results, which agree much better with previous microarray studies and the known biology than the results of an uncorrected analysis. (read more… )

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What is RNA-Seq?

long RNAs are first converted into a library of cDNA fragments through either RNA fragmentation or DNA fragmentation. Sequencing adaptors (blue) are subsequently added to each cDNA fragment and a short sequence is obtained from each cDNA using high-throughput sequencing technology. The resulting sequence reads are aligned with the reference genome or transcriptome, and classified as three types: exonic reads, junction reads and poly(A) end-reads. These three types are used to generate a base-resolution expression profile for each gene. Nat Rev Genet 10(1):57-63 (2009)